Maximum-Service Channel Assignment in Vehicular Radar-Communication
Maximum-Service Channel Assignment in Vehicular Radar-Communication
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DOI：
10.1109/access.2021.3118964
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发表时间：
2021
期刊：
影响因子：
3.9
通讯作者：
Mai Kafafy;A. Ibrahim;M. H. Ismail
中科院分区：
文献类型：
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作者：
Mai Kafafy;A. Ibrahim;M. H. Ismail
由于越来越多的连接设备和应用程序都希望同时访问频谱，射频频谱变得比以往任何时候都更加拥挤，因此不同技术之间的频谱共享已成为必要。车载网络是频谱共享的众多方案之一，因为车辆预计将共享相同的频谱，用于雷达传感和通信目的。在汽车系统中，雷达传感器和通信收发机之间的信道分配对未来车载网络的成功至关重要。提出了一种在服务质量要求较高的情况下，以最大化服务车辆数量为目标的多台车载雷达和通信收发机的信道分配优化框架。将信道分配问题描述为带二元变量的整数线性优化问题。提出了一种基于有序顺序信道分配(OSCA)的启发式算法，该算法的计算复杂度和运行时间比基于分支切割的算法至少高出92%，最多达到分支切割算法运行时间的2%。
Spectrum sharing between different technologies has become a necessity as the RF spectrum has become more congested than ever due to the increasing number of connected devices and applications all wishing to access the spectrum simultaneously. Vehicular networks are one of many scenarios of spectrum sharing as vehicles are expected to share the same spectrum for radar sensing and communication purposes. Channel assignment among radar sensors and communication transceivers in automotive systems is crucial for the success of future vehicular networks. This paper proposes an optimization framework for the channel assignment to multiple automotive radars and communication transceivers aiming at maximizing the number of served vehicles under hard quality of service requirements. The channel assignment problem is formulated as an integer linear optimization with binary variables. A heuristic solution that is based on ordered sequential channel assignment (OSCA) is proposed and is shown to achieve at least 92% of the solution obtained from branch-and-cut based techniques with much less computational complexity and run-time; at most 2% of the run-time of branch-and-cut.